{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2 as cv2\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "img = cv2.imread(\"car.png\",cv2.IMREAD_GRAYSCALE)\n",
    "plt.imshow(img,cmap=\"gray\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ret,img = cv2.threshold(img,175,255,cv2.THRESH_BINARY)# 大于127为255，小于127为0\n",
    "plt.imshow(img,cmap=\"gray\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "result=[] # result 用于判读该列是否属于字符的一部分，如果该列没有字符则值为0\n",
    "for col in range(img.shape[1]):\n",
    "    result.append(0)\n",
    "    for row in range(img.shape[0]):\n",
    "        result[col] = result[col]+img[row][col]/255"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "character_dict={} # 存储字符起始列的位置\n",
    "num=0 #字符数\n",
    "i=0 # 当前指向的列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "while i < len(result):\n",
    "    if result[i] == 0: # 该列没有字符\n",
    "        i += 1\n",
    "    else:\n",
    "        index = i + 1  #该列有字符，index遍历寻找字符结束位置\n",
    "        while result[index] != 0:\n",
    "            index += 1\n",
    "        character_dict[num] = [i, index-1]\n",
    "        num += 1\n",
    "        i = index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{0: [17, 86],\n",
       " 1: [110, 178],\n",
       " 2: [204, 216],\n",
       " 3: [240, 311],\n",
       " 4: [335, 406],\n",
       " 5: [430, 503],\n",
       " 6: [528, 602],\n",
       " 7: [629, 706]}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "character_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 7 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 分割字符，第3个字符为点，舍弃\n",
    "for i in range(8):\n",
    "    if i==2:\n",
    "        continue\n",
    "    padding = (170 - (character_dict[i][1] - character_dict[i][0])) / 2 #高度170，宽度也应该是170\n",
    "    character = np.pad(img[:,character_dict[i][0]:character_dict[i][1]], ((0,0), (int(padding), int(padding))), 'constant', constant_values=(0,0))# 填充字符的宽度\n",
    "    #character = cv2.resize(character, (20,20))\n",
    "    plt.subplot(1,8,i+1)\n",
    "    plt.imshow(character,cmap=\"gray\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
